abstract = "We propose how Genetic Programming (GP) can be used
for developing, in real time, problem-specific
heuristics for Branch and Bound (B&B) search. A GP run,
embedded into the B&B process, exploits the
characteristics of the particular problem being solved,
evolving a problem-specific heuristic expression. The
evolved heuristic replaces the default one for the rest
of the B&B search. The application of our method to
node selection for B&B based Mixed Integer Programming
is illustrated by incorporating the GP node selection
heuristic generator into a B&B MIP solver. The hybrid
system compares well with the unmodified solver using
DFS, BFS, or even the advanced Best Projection
heuristic when confronted with hard MIP problems from
the MIPLIB3 benchmarking suite.",